feat: 第一次上传代码

node_modules/lottie-web/player/js/3rd_party/BezierEaser.js

@@ -0,0 +1,158 @@
+/* eslint-disable */
+const BezierFactory = (function () {
+  /**
+     * BezierEasing - use bezier curve for transition easing function
+     * by Gaëtan Renaudeau 2014 - 2015 – MIT License
+     *
+     * Credits: is based on Firefox's nsSMILKeySpline.cpp
+     * Usage:
+     * var spline = BezierEasing([ 0.25, 0.1, 0.25, 1.0 ])
+     * spline.get(x) => returns the easing value | x must be in [0, 1] range
+     *
+     */
+
+  var ob = {};
+  ob.getBezierEasing = getBezierEasing;
+  var beziers = {};
+
+  function getBezierEasing(a, b, c, d, nm) {
+    var str = nm || ('bez_' + a + '_' + b + '_' + c + '_' + d).replace(/\./g, 'p');
+    if (beziers[str]) {
+      return beziers[str];
+    }
+    var bezEasing = new BezierEasing([a, b, c, d]);
+    beziers[str] = bezEasing;
+    return bezEasing;
+  }
+
+  // These values are established by empiricism with tests (tradeoff: performance VS precision)
+  var NEWTON_ITERATIONS = 4;
+  var NEWTON_MIN_SLOPE = 0.001;
+  var SUBDIVISION_PRECISION = 0.0000001;
+  var SUBDIVISION_MAX_ITERATIONS = 10;
+
+  var kSplineTableSize = 11;
+  var kSampleStepSize = 1.0 / (kSplineTableSize - 1.0);
+
+  var float32ArraySupported = typeof Float32Array === 'function';
+
+  function A(aA1, aA2) { return 1.0 - 3.0 * aA2 + 3.0 * aA1; }
+  function B(aA1, aA2) { return 3.0 * aA2 - 6.0 * aA1; }
+  function C(aA1) { return 3.0 * aA1; }
+
+  // Returns x(t) given t, x1, and x2, or y(t) given t, y1, and y2.
+  function calcBezier(aT, aA1, aA2) {
+    return ((A(aA1, aA2) * aT + B(aA1, aA2)) * aT + C(aA1)) * aT;
+  }
+
+  // Returns dx/dt given t, x1, and x2, or dy/dt given t, y1, and y2.
+  function getSlope(aT, aA1, aA2) {
+    return 3.0 * A(aA1, aA2) * aT * aT + 2.0 * B(aA1, aA2) * aT + C(aA1);
+  }
+
+  function binarySubdivide(aX, aA, aB, mX1, mX2) {
+    var currentX,
+      currentT,
+      i = 0;
+    do {
+      currentT = aA + (aB - aA) / 2.0;
+      currentX = calcBezier(currentT, mX1, mX2) - aX;
+      if (currentX > 0.0) {
+        aB = currentT;
+      } else {
+        aA = currentT;
+      }
+    } while (Math.abs(currentX) > SUBDIVISION_PRECISION && ++i < SUBDIVISION_MAX_ITERATIONS);
+    return currentT;
+  }
+
+  function newtonRaphsonIterate(aX, aGuessT, mX1, mX2) {
+    for (var i = 0; i < NEWTON_ITERATIONS; ++i) {
+      var currentSlope = getSlope(aGuessT, mX1, mX2);
+      if (currentSlope === 0.0) return aGuessT;
+      var currentX = calcBezier(aGuessT, mX1, mX2) - aX;
+      aGuessT -= currentX / currentSlope;
+    }
+    return aGuessT;
+  }
+
+  /**
+     * points is an array of [ mX1, mY1, mX2, mY2 ]
+     */
+  function BezierEasing(points) {
+    this._p = points;
+    this._mSampleValues = float32ArraySupported ? new Float32Array(kSplineTableSize) : new Array(kSplineTableSize);
+    this._precomputed = false;
+
+    this.get = this.get.bind(this);
+  }
+
+  BezierEasing.prototype = {
+
+    get: function (x) {
+      var mX1 = this._p[0],
+        mY1 = this._p[1],
+        mX2 = this._p[2],
+        mY2 = this._p[3];
+      if (!this._precomputed) this._precompute();
+      if (mX1 === mY1 && mX2 === mY2) return x; // linear
+      // Because JavaScript number are imprecise, we should guarantee the extremes are right.
+      if (x === 0) return 0;
+      if (x === 1) return 1;
+      return calcBezier(this._getTForX(x), mY1, mY2);
+    },
+
+    // Private part
+
+    _precompute: function () {
+      var mX1 = this._p[0],
+        mY1 = this._p[1],
+        mX2 = this._p[2],
+        mY2 = this._p[3];
+      this._precomputed = true;
+      if (mX1 !== mY1 || mX2 !== mY2) { this._calcSampleValues(); }
+    },
+
+    _calcSampleValues: function () {
+      var mX1 = this._p[0],
+        mX2 = this._p[2];
+      for (var i = 0; i < kSplineTableSize; ++i) {
+        this._mSampleValues[i] = calcBezier(i * kSampleStepSize, mX1, mX2);
+      }
+    },
+
+    /**
+         * getTForX chose the fastest heuristic to determine the percentage value precisely from a given X projection.
+         */
+    _getTForX: function (aX) {
+      var mX1 = this._p[0],
+        mX2 = this._p[2],
+        mSampleValues = this._mSampleValues;
+
+      var intervalStart = 0.0;
+      var currentSample = 1;
+      var lastSample = kSplineTableSize - 1;
+
+      for (; currentSample !== lastSample && mSampleValues[currentSample] <= aX; ++currentSample) {
+        intervalStart += kSampleStepSize;
+      }
+      --currentSample;
+
+      // Interpolate to provide an initial guess for t
+      var dist = (aX - mSampleValues[currentSample]) / (mSampleValues[currentSample + 1] - mSampleValues[currentSample]);
+      var guessForT = intervalStart + dist * kSampleStepSize;
+
+      var initialSlope = getSlope(guessForT, mX1, mX2);
+      if (initialSlope >= NEWTON_MIN_SLOPE) {
+        return newtonRaphsonIterate(aX, guessForT, mX1, mX2);
+      } if (initialSlope === 0.0) {
+        return guessForT;
+      }
+      return binarySubdivide(aX, intervalStart, intervalStart + kSampleStepSize, mX1, mX2);
+    },
+  };
+
+  return ob;
+}());
+
+export default BezierFactory;